Carnegie Mellon University and NVIDIA have teamed up to develop a new training technique that enables humanoid robots to perform complex athletic movements with unprecedented agility—from Cristiano Ronaldo’s signature mid-air spin celebration to Kobe Bryant’s fadeaway jump shot.

The framework, Aligning Simulation and Real Physics (ASAP), bridges a critical gap between simulation and reality by allowing humanoid robots to execute high-level athletic movements previously thought too complex for machines.

“Humanoid robots hold the potential for unparalleled versatility for performing human-like, whole-body skills,” the researchers noted in their paper. “However, achieving agile and coordinated whole-body motions remains a significant challenge due to the dynamics mismatch between simulation and the real world.”

ASAP tackles this challenge through a two-stage process.

First, it pre-trains motion tracking policies—the algorithmic rules that control the tracking—in simulation using human motion data. It then deploys these policies in the real world to collect data that helps bridge the gap between simulated and actual physics.

The result is a humanoid robot capable of rep

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Author: Jose Antonio Lanz

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